Intelligent test method and system for cluster server

Abstract

The invention is suitable for the technical field of cluster servers, and provides an intelligent test method and system for a cluster server. The method comprises the following steps: performing real-time monitoring and virtual test matching on a target cluster server, and intercepting virtual test data; extracting test demand data; performing virtual test analysis, and calculating an execution performance value and a queuing performance value of the target cluster server; and performing test comparison analysis on the execution performance value and the queuing performance value to generate test feedback information. Real-time monitoring data can be subjected to virtual test matching, virtual test data interception, test demand data extraction, virtual test analysis and calculation of an execution performance value and a queuing performance value, test feedback information is generated through test comparison analysis, daily operation of a cluster server does not need to be paused, and the test efficiency is improved. According to the method, the independent test time period is specially arranged for related detection, the test process is simple and professional, the availability of the cluster server is effectively guaranteed, and the test efficiency of the cluster server is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of cluster servers, and in particular relates to an intelligent testing method and system for cluster servers. Background Art

[0002] Cluster server is a form of server organization that connects multiple servers through a network and works together to achieve high performance, high availability and scalability. It is mainly used in cloud computing, big data processing, website hosting and virtualization scenarios.

[0003] Cluster server testing is an activity to verify and evaluate the cluster server system.

[0004] In the prior art, testing of cluster servers that have been put into operation often requires suspending the daily operation of the cluster servers and arranging an independent testing period to conduct relevant tests. The testing process is cumbersome and complicated, and requires a lot of time for recording and analysis, which not only affects the normal business operation of the cluster servers and reduces the availability of the cluster servers, but also has obvious deficiencies in testing efficiency. Summary of the invention

[0005] The purpose of the embodiments of the present invention is to provide an intelligent testing method and system for a cluster server, aiming to solve the technical problems existing in the prior art mentioned in the background technology.

[0006] The embodiment of the present invention is implemented as follows:

[0007] An intelligent testing method for a cluster server, the method specifically comprising the following steps:

[0008] Performing real-time monitoring on the target cluster server, acquiring real-time monitoring data, and performing virtual test matching on the real-time monitoring data to intercept virtual test data;

[0009] Identify the data type of the virtual test data, and extract test requirement data from the virtual test data;

[0010] Perform virtual test analysis according to the test requirement data to calculate the execution performance value and queuing performance value of the target cluster server;

[0011] Based on preset standard performance data, the execution performance value and the queuing performance value are tested, compared and analyzed to generate test feedback information.

[0012] As a further limitation of the technical solution of the embodiment of the present invention, the real-time monitoring of the target cluster server, obtaining the real-time monitoring data, and performing virtual test matching on the real-time monitoring data, and intercepting the virtual test data specifically include the following steps:

[0013] Determine the target cluster server with test requirements;

[0014] Performing real-time monitoring and recording on the target cluster server to obtain real-time monitoring data;

[0015] Performing virtual test matching on the real-time monitoring data to determine a test matching period;

[0016] According to the test matching period, virtual test data is intercepted from the real-time monitoring data.

[0017] As a further limitation of the technical solution of the embodiment of the present invention, the virtual test matching of the real-time monitoring data and determining the test matching period specifically include the following steps:

[0018] Performing task matching on the real-time monitoring data to determine a task matching period with a single task;

[0019] Performing operation matching on the real-time monitoring data to determine a complete operation matching period;

[0020] Determining a plurality of overlapping time periods according to the task matching time period and the operation matching time period;

[0021] According to the preset time period requirement, a test matching time period is selected from the multiple overlapping time periods.

[0022] As a further limitation of the technical solution of the embodiment of the present invention, the step of identifying the data type of the virtual test data and extracting the test requirement data from the virtual test data specifically comprises the following steps:

[0023] Identifying the virtual test data and determining a test task;

[0024] Identifying multiple test requests corresponding to the test task;

[0025] Extracting relevant test data from the virtual test data according to the plurality of test requests;

[0026] According to the preset multiple types of requirement data, test requirement data is extracted from the relevant test data.

[0027] As a further limitation of the technical solution of the embodiment of the present invention, performing virtual test analysis according to the test requirement data and calculating the execution performance value and the queuing performance value of the target cluster server specifically includes the following steps:

[0028] Performing a request service analysis of the virtual test according to the test demand data to obtain a request service rate;

[0029] According to the test demand data, perform request arrival analysis of the virtual test to obtain the request arrival rate;

[0030] Based on the test requirement data, calculating the execution performance value of the target cluster server;

[0031] Based on the request service rate and the request arrival rate, a queuing performance value of the target cluster server is calculated.

[0032] As a further limitation of the technical solution of the embodiment of the present invention, the calculation formula of the execution performance value is:

[0033]

[0034] Where A is the execution performance value, i represents the i-th test request, n is the total number of test requests, Tr i is the response time of the ith test request, Ts i The service time for the i-th test request;

[0035] The calculation formula of the queuing performance value is:

[0036]

[0037] Among them, B is the queuing performance value, μ is the request service rate, and λ is the request arrival rate.

[0038] As a further limitation of the technical solution of the embodiment of the present invention, the test comparison and analysis of the execution performance value and the queuing performance value based on the preset standard performance data to generate the test feedback information specifically includes the following steps:

[0039] Based on the preset standard performance data, test and compare the execution performance value and the queuing performance value, and record the test comparison results;

[0040] Import test feedback template;

[0041] The test comparison results are sorted and filled according to the test feedback template to generate test feedback information.

[0042] An intelligent testing system for a cluster server, the system comprises a real-time monitoring processing module, a test data extraction module, a virtual test analysis module and a test comparison analysis module, wherein:

[0043] A real-time monitoring processing module is used to perform real-time monitoring on the target cluster server, obtain real-time monitoring data, perform virtual test matching on the real-time monitoring data, and intercept virtual test data;

[0044] A test data extraction module, used to identify the data type of the virtual test data and extract test requirement data from the virtual test data;

[0045] A virtual test analysis module, used to perform virtual test analysis according to the test requirement data, and calculate the execution performance value and queuing performance value of the target cluster server;

[0046] The test comparison and analysis module is used to perform test comparison and analysis on the execution performance value and the queuing performance value based on preset standard performance data to generate test feedback information.

[0047] As a further limitation of the technical solution of the embodiment of the present invention, the real-time monitoring processing module specifically includes:

[0048] A cluster server determination unit, used to determine a target cluster server having a test requirement;

[0049] A monitoring and recording unit, used to monitor and record the target cluster server in real time to obtain real-time monitoring data;

[0050] A virtual test matching unit, used to perform virtual test matching on the real-time monitoring data and determine a test matching period;

[0051] The data interception unit is used to intercept virtual test data from the real-time monitoring data according to the test matching period.

[0052] As a further limitation of the technical solution of the embodiment of the present invention, the test data extraction module specifically includes:

[0053] A task identification unit, used to identify the virtual test data and determine the test task;

[0054] A request identification unit, used to identify multiple test requests corresponding to the test task;

[0055] A related test data extraction unit, configured to extract related test data from the virtual test data according to the plurality of test requests;

[0056] The test requirement data extraction unit is used to extract the test requirement data from the relevant test data according to a plurality of preset requirement data types.

[0057] Compared with the prior art, the present invention has the following beneficial effects:

[0058] The embodiment of the present invention performs real-time monitoring and virtual test matching on the target cluster server, intercepts virtual test data; extracts test requirement data; performs virtual test analysis, calculates the execution performance value and queuing performance value of the target cluster server; performs test comparison analysis on the execution performance value and the queuing performance value, and generates test feedback information. It is possible to perform virtual test matching on real-time monitoring data, intercept virtual test data, extract test requirement data, perform virtual test analysis, calculate the execution performance value and the queuing performance value, and generate test feedback information by performing test comparison analysis. There is no need to suspend the daily operation of the cluster server, and an independent test period is specially arranged for related detection. The test process is simple and professional, which effectively guarantees the availability of the cluster server and improves the efficiency of cluster server testing. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 A flow chart of an intelligent testing method for a cluster server provided by an embodiment of the present invention is shown;

[0060] Figure 2 A flowchart of capturing virtual test data in a method provided by an embodiment of the present invention is shown;

[0061] Figure 3 A flowchart of performing virtual test matching in the method provided by an embodiment of the present invention is shown;

[0062] Figure 4 A flowchart of extracting test requirement data in the method provided by an embodiment of the present invention is shown;

[0063] Figure 5 A flowchart of performing virtual test analysis in a method provided by an embodiment of the present invention is shown;

[0064] Figure 6 A flowchart of performing test comparison and analysis in the method provided by an embodiment of the present invention is shown;

[0065] Figure 7 An application architecture diagram of an intelligent testing system for a cluster server provided by an embodiment of the present invention is shown;

[0066] Figure 8 It shows a structural block diagram of a real-time monitoring processing module in a system provided by an embodiment of the present invention;

[0067] Fig. 9 The structure block diagram of the test data extraction module in the system provided by the embodiment of the present invention is shown. DETAILED DESCRIPTION

[0068] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0069] It is understandable that in the prior art, testing of cluster servers that have been put into operation often requires suspending the daily operation of the cluster servers and arranging an independent testing period to conduct relevant tests. In addition, the testing process is cumbersome and complicated, and requires a lot of time for recording and analysis, which not only affects the normal business operation of the cluster servers and reduces the availability of the cluster servers, but also has obvious deficiencies in testing efficiency.

[0070] To solve the above problems, an intelligent testing method and system for a cluster server disclosed in an embodiment of the present invention performs real-time monitoring of a target cluster server, obtains real-time monitoring data, performs virtual test matching on the real-time monitoring data, and intercepts virtual test data; identifies the data type of the virtual test data, and extracts test requirement data from the virtual test data; performs virtual test analysis based on the test requirement data, and calculates the execution performance value and queuing performance value of the target cluster server; performs test comparison and analysis on the execution performance value and the queuing performance value based on preset standard performance data, and generates test feedback information. It is possible to perform virtual test matching on the real-time monitoring data, intercept virtual test data, extract test requirement data, perform virtual test analysis, calculate the execution performance value and the queuing performance value, and generate test feedback information by performing test comparison and analysis. There is no need to suspend the daily operation of the cluster server, and an independent test period is specially arranged for related detection. The test process is simple and professional, which effectively guarantees the availability of the cluster server and improves the efficiency of cluster server testing.

[0071] Specifically, Figure 1 The flowchart of the intelligent testing method of the cluster server provided by the embodiment of the present invention is shown.

[0072] In a preferred embodiment of the present invention, a cluster server intelligent testing method is provided, the method specifically comprising the following steps:

[0073] Step S101: monitor the target cluster server in real time to obtain real-time monitoring data, perform virtual test matching on the real-time monitoring data, and intercept virtual test data.

[0074] In an embodiment of the present invention, a target cluster server with a test requirement is determined, and real-time monitoring data is obtained by real-time monitoring and recording of the operating status, task processing, node status, business indicators, etc. used in daily operations of the target cluster server. Task matching is then performed on the real-time monitoring data to determine a working period in which the target cluster server only executes a single task, which is marked as a task matching period. Operation matching is performed on the real-time monitoring data to determine a working period in which all nodes in the target cluster server are in an operating state, which is marked as an operation matching period. Time period overlap analysis is performed on the task matching period and the operation matching period to determine multiple overlapping time periods that simultaneously meet the task matching period and the operation matching period. Then, according to the preset time period requirement, an overlapping time period that meets the time period requirement is selected from the multiple overlapping time periods, and marked as a test matching period. Then, according to the test matching period, virtual test data is intercepted from the real-time monitoring data.

[0075] It can be understood that the time period requirements may include the time period length requirements and the time requirements from the current time (for example: the time period length is 1 to 2 hours, and no more than 30 days from the current time), so that the selected test matching time period has both a certain length of test research and the freshness of being not far from the current time.

[0076] Specifically, Figure 2 A flow chart of capturing virtual test data in the method provided by an embodiment of the present invention is shown.

[0077] Among them, in another preferred embodiment provided by the present invention, the target cluster server is monitored in real time, real-time monitoring data is obtained, and virtual test matching is performed on the real-time monitoring data, and intercepting virtual test data specifically includes the following steps:

[0078] Step S1011: Determine a target cluster server that has a test requirement.

[0079] Step S1012: monitor and record the target cluster server in real time to obtain real-time monitoring data.

[0080] Step S1013: Perform virtual test matching on the real-time monitoring data to determine a test matching period.

[0081] Specifically, Figure 3 A flow chart of virtual test matching in the method provided by an embodiment of the present invention is shown.

[0082] In another preferred embodiment of the present invention, the performing virtual test matching on the real-time monitoring data and determining the test matching period specifically comprises the following steps:

[0083] Step S10131: performing task matching on the real-time monitoring data to determine a task matching period with a single task.

[0084] Step S10132: perform operation matching on the real-time monitoring data to determine a complete operation matching period.

[0085] Step S10133: Determine a plurality of overlapping time periods according to the task matching time period and the operation matching time period.

[0086] Step S10134: Select a test matching time period from the multiple overlapping time periods according to the preset time period requirement.

[0087] Furthermore, the target cluster server is monitored in real time, real-time monitoring data is obtained, and virtual test matching is performed on the real-time monitoring data, and intercepting virtual test data also includes the following steps:

[0088] Step S1014: extract virtual test data from the real-time monitoring data according to the test matching period.

[0089] Furthermore, the intelligent testing method of the cluster server also includes the following steps:

[0090] Step S102: Identify the data type of the virtual test data, and extract test requirement data from the virtual test data.

[0091] In an embodiment of the present invention, virtual test data is identified to determine the operational tasks performed by the target cluster server during the test matching period, and marked as test tasks. Since the cluster server coordinates and distributes the tasks to form multiple requests and send them to multiple nodes, multiple test requests corresponding to the test tasks can be identified, and then relevant test data can be extracted from the virtual test data according to the multiple test requests, and then test requirement data can be extracted from the relevant test data according to the preset multiple requirement data types.

[0092] It can be understood that the extraction of relevant test data is a process of preliminary screening of virtual test data, which can eliminate data in the virtual test data that is not related to the test request; the extraction of test requirement data is a further screening of relevant test data, which can eliminate data that is not related to multiple requirement data types.

[0093] It can be understood that the test task is actually an execution task in the daily operation of the target cluster server; the test request is actually an execution request for coordinating and distributing the execution task in the daily operation of the target cluster server.

[0094] Specifically, Figure 4A flow chart of extracting test requirement data in the method provided by an embodiment of the present invention is shown.

[0095] In another preferred embodiment of the present invention, the step of identifying the data type of the virtual test data and extracting the test requirement data from the virtual test data specifically comprises the following steps:

[0096] Step S1021: Identify the virtual test data and determine the test task.

[0097] Step S1022: Identify multiple test requests corresponding to the test task.

[0098] Step S1023: extract relevant test data from the virtual test data according to the multiple test requests.

[0099] Step S1024: extract test requirement data from the relevant test data according to the preset multiple requirement data types.

[0100] Furthermore, the intelligent testing method of the cluster server also includes the following steps:

[0101] Step S103: Perform virtual test analysis according to the test requirement data to calculate the execution performance value and queuing performance value of the target cluster server.

[0102] In the embodiment of the present invention, according to the test demand data, a request service analysis of the virtual test is performed to obtain the request service rate, and a request arrival analysis of the virtual test is performed to obtain the request arrival rate. Based on the test demand data, the execution performance value of the target cluster server is calculated, and based on the request service rate and the request arrival rate, the queuing performance value of the target cluster server is calculated. Specifically, the calculation formula of the execution performance value is:

[0103]

[0104] Where A is the execution performance value, i represents the i-th test request, n is the total number of test requests, Tr i is the response time of the ith test request, Ts i The service time for the i-th test request;

[0105] The calculation formula of the queue performance value is:

[0106]

[0107] Among them, B is the queuing performance value, μ is the request service rate, and λ is the request arrival rate.

[0108] It can be understood that the request service rate is the average number of test request services (executed) per unit time; the request arrival rate is the average number of test requests arriving at the corresponding server nodes of the target cluster server per unit time.

[0109] It can be understood that the execution performance value is related to the load balancing performance of the target cluster server. The larger the execution performance value, the heavier the load on the target cluster server; the smaller the execution performance value, the lighter the load on the target cluster server. Therefore, the smaller the execution performance value, the better the load balancing performance of the target cluster server. Testing and analyzing the target cluster server through the execution performance value can solve the problem of large differences in service time for different requests and unfair performance evaluation directly based on response time.

[0110] It can be understood that the queuing performance value is related to the request queue residence time of multiple test requests in the target cluster server, and can reflect the request processing efficiency of the target cluster server. The larger the queuing performance value, the higher the request processing efficiency of the target cluster server; the smaller the queuing performance value, the lower the request processing efficiency of the target cluster server.

[0111] Specifically, Figure 5 A flow chart of performing virtual test analysis in the method provided by an embodiment of the present invention is shown.

[0112] Among them, in another preferred implementation manner provided by the present invention, performing virtual test analysis according to the test requirement data and calculating the execution performance value and the queuing performance value of the target cluster server specifically includes the following steps:

[0113] Step S1031: Perform request service analysis of the virtual test according to the test demand data to obtain a request service rate.

[0114] Step S1032: Perform request arrival analysis of the virtual test according to the test requirement data to obtain the request arrival rate.

[0115] Step S1033: Calculate the execution performance value of the target cluster server based on the test requirement data.

[0116] Step S1034: Calculate the queuing performance value of the target cluster server based on the request service rate and the request arrival rate.

[0117] Furthermore, the intelligent testing method of the cluster server also includes the following steps:

[0118] Step S104: Based on preset standard performance data, test and compare the execution performance value and the queuing performance value to generate test feedback information.

[0119] In an embodiment of the present invention, based on preset standard performance data, the test values ​​of the execution performance value and the queuing performance value are compared, and the test comparison results are recorded. By importing a test feedback template and taking the test feedback template as a basis, the test comparison results are sorted and filled with content to generate test feedback information, and the test feedback information is displayed when there is a browsing demand.

[0120] It can be understood that by directly comparing the test values ​​of the execution performance value and the queuing performance value, the test is simple and professional, which can accurately reflect the load balancing performance and request processing efficiency of the target cluster server, effectively avoiding the tedious and complicated testing process, and does not require a lot of time for recording and analysis, thereby realizing fast and accurate intelligent testing of cluster servers.

[0121] Specifically, Figure 6 A flow chart of performing test comparison and analysis in the method provided by an embodiment of the present invention is shown.

[0122] Among them, in another preferred embodiment provided by the present invention, the test comparison and analysis of the execution performance value and the queuing performance value based on the preset standard performance data to generate the test feedback information specifically includes the following steps:

[0123] Step S1041: Based on preset standard performance data, test and compare the execution performance value and the queuing performance value, and record the test comparison results.

[0124] Step S1042: import the test feedback template.

[0125] Step S1043: sort and fill the test comparison results according to the test feedback template to generate test feedback information.

[0126] Furthermore, Figure 7 The application architecture diagram of the intelligent testing system of the cluster server provided by the embodiment of the present invention is shown.

[0127] Specifically, in another preferred embodiment of the present invention, an intelligent testing system for a cluster server includes:

[0128] The real-time monitoring processing module 101 is used to perform real-time monitoring on the target cluster server, obtain real-time monitoring data, perform virtual test matching on the real-time monitoring data, and intercept virtual test data.

[0129] In an embodiment of the present invention, the real-time monitoring and processing module 101 determines a target cluster server with a test requirement, obtains real-time monitoring data by real-time monitoring and recording the operating status, task processing, node status, business indicators, etc. used in daily operations of the target cluster server, and then performs task matching on the real-time monitoring data to determine a working period in which the target cluster server only performs a single task, which is marked as a task matching period, and performs operation matching on the real-time monitoring data to determine a working period in which all nodes in the target cluster server are in an operating state, which is marked as an operation matching period, performs time period overlap analysis on the task matching period and the operation matching period, determines multiple overlapping time periods that simultaneously meet the task matching period and the operation matching period, and then selects an overlapping time period that meets the time period requirements from multiple overlapping time periods according to the preset time period requirements, and marks it as a test matching period, and then intercepts virtual test data from the real-time monitoring data according to the test matching period.

[0130] Furthermore, Figure 8 It shows a structural block diagram of the real-time monitoring processing module 101 in the system provided by the embodiment of the present invention.

[0131] Specifically, in another preferred embodiment provided by the present invention, the real-time monitoring processing module 101 specifically includes:

[0132] The cluster server determining unit 1011 is used to determine a target cluster server having a test requirement.

[0133] The monitoring and recording unit 1012 is used to monitor and record the target cluster server in real time to obtain real-time monitoring data.

[0134] The virtual test matching unit 1013 is used to perform virtual test matching on the real-time monitoring data to determine a test matching period.

[0135] The data interception unit 1014 is used to intercept virtual test data from the real-time monitoring data according to the test matching period.

[0136] Furthermore, the intelligent testing system of the cluster server also includes:

[0137] The test data extraction module 102 is used to identify the data type of the virtual test data and extract test requirement data from the virtual test data.

[0138] In an embodiment of the present invention, the test data extraction module 102 identifies the virtual test data, determines the operational tasks performed by the target cluster server in the test matching period, and marks them as test tasks. Since the cluster server coordinates and distributes the tasks, forms multiple requests and sends them to multiple nodes, it is possible to identify multiple test requests corresponding to the test tasks, and then extract relevant test data from the virtual test data according to the multiple test requests, and then extract test requirement data from the relevant test data according to the preset multiple requirement data types.

[0139] Furthermore, Fig. 9 It shows a structural block diagram of the test data extraction module 102 in the system provided by the embodiment of the present invention.

[0140] Specifically, in another preferred embodiment provided by the present invention, the test data extraction module 102 specifically includes:

[0141] The task identification unit 1021 is used to identify the virtual test data and determine the test task.

[0142] The request identification unit 1022 is used to identify multiple test requests corresponding to the test task.

[0143] The relevant test data extraction unit 1023 is used to extract relevant test data from the virtual test data according to the multiple test requests.

[0144] The test requirement data extraction unit 1024 is used to extract the test requirement data from the relevant test data according to a plurality of preset requirement data types.

[0145] Furthermore, the intelligent testing system of the cluster server also includes:

[0146] The virtual test analysis module 103 is used to perform virtual test analysis according to the test requirement data, and calculate the execution performance value and the queuing performance value of the target cluster server.

[0147] In the embodiment of the present invention, the virtual test analysis module 103 performs a request service analysis of the virtual test according to the test requirement data to obtain the request service rate, and performs a request arrival analysis of the virtual test to obtain the request arrival rate, calculates the execution performance value of the target cluster server based on the test requirement data, and calculates the queuing performance value of the target cluster server based on the request service rate and the request arrival rate. Specifically, the calculation formula of the execution performance value is:

[0148]

[0149] Where A is the execution performance value, i represents the i-th test request, n is the total number of test requests, Tr i is the response time of the ith test request, Ts i The service time for the i-th test request;

[0150] The calculation formula of the queue performance value is:

[0151]

[0152] Among them, B is the queuing performance value, μ is the request service rate, and λ is the request arrival rate.

[0153] The test comparison and analysis module 104 is used to perform a test comparison and analysis on the execution performance value and the queuing performance value based on preset standard performance data to generate test feedback information.

[0154] In an embodiment of the present invention, the test comparison and analysis module 104 compares the test values ​​of the execution performance value and the queuing performance value based on preset standard performance data, and records the test comparison results. By importing the test feedback template and taking the test feedback template as the basis, the test comparison results are sorted and filled with content to generate test feedback information, and the test feedback information is displayed when there is a browsing demand.

[0155] It should be understood that, although each step in the flow chart of each embodiment of the present invention is shown in sequence according to the indication of the arrow, these steps are not necessarily performed in sequence according to the order indicated by the arrow. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be performed in other orders. Moreover, at least a portion of the steps in each embodiment may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these sub-steps or stages is not necessarily performed in sequence, but can be performed in turn or alternately with at least a portion of other steps or sub-steps or stages of other steps.

[0156] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0157] The above-mentioned embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims

1. An intelligent testing method for a cluster server, characterized in that: The method specifically comprises the following steps: Performing real-time monitoring on the target cluster server, acquiring real-time monitoring data, and performing virtual test matching on the real-time monitoring data to intercept virtual test data; Identify the data type of the virtual test data, and extract test requirement data from the virtual test data; Perform virtual test analysis according to the test requirement data to calculate the execution performance value and queuing performance value of the target cluster server; Based on preset standard performance data, the execution performance value and the queuing performance value are tested, compared and analyzed to generate test feedback information.

2. The intelligent testing method for cluster servers according to claim 1, characterized in that: The real-time monitoring of the target cluster server, obtaining the real-time monitoring data, and performing virtual test matching on the real-time monitoring data, and intercepting the virtual test data specifically include the following steps: Determine the target cluster server with test requirements; Performing real-time monitoring and recording on the target cluster server to obtain real-time monitoring data; Performing virtual test matching on the real-time monitoring data to determine a test matching period; According to the test matching period, virtual test data is intercepted from the real-time monitoring data.

3. The intelligent testing method for cluster servers according to claim 2, characterized in that: The virtual test matching of the real-time monitoring data and determining the test matching period specifically include the following steps: Performing task matching on the real-time monitoring data to determine a task matching period with a single task; Performing operation matching on the real-time monitoring data to determine a complete operation matching period; Determining a plurality of overlapping time periods according to the task matching time period and the operation matching time period; According to the preset time period requirement, a test matching time period is selected from the multiple overlapping time periods.

4. The intelligent testing method for cluster servers according to claim 1, characterized in that: The step of identifying the data type of the virtual test data and extracting the test requirement data from the virtual test data specifically comprises the following steps: Identifying the virtual test data and determining a test task; Identifying multiple test requests corresponding to the test task; Extracting relevant test data from the virtual test data according to the plurality of test requests; According to the preset multiple types of requirement data, test requirement data is extracted from the relevant test data.

5. The intelligent testing method for cluster servers according to claim 4, characterized in that: The performing of virtual test analysis according to the test requirement data to calculate the execution performance value and the queuing performance value of the target cluster server specifically includes the following steps: Performing a request service analysis of the virtual test according to the test demand data to obtain a request service rate; According to the test demand data, perform request arrival analysis of the virtual test to obtain the request arrival rate; Based on the test requirement data, calculating the execution performance value of the target cluster server; Based on the request service rate and the request arrival rate, a queuing performance value of the target cluster server is calculated.

6. The intelligent testing method for cluster servers according to claim 5, characterized in that: The calculation formula of the execution performance value is: Where A is the execution performance value, i represents the i-th test request, n is the total number of test requests, Tr i is the response time of the i-th test request, Ts i The service time for the i-th test request; The calculation formula of the queuing performance value is: Among them, B is the queuing performance value, μ is the request service rate, and λ is the request arrival rate.

7. The intelligent testing method for cluster servers according to claim 1, characterized in that: The test comparison and analysis of the execution performance value and the queuing performance value based on the preset standard performance data to generate the test feedback information specifically includes the following steps: Based on the preset standard performance data, test and compare the execution performance value and the queuing performance value, and record the test comparison results; Import test feedback template; The test comparison results are sorted and filled according to the test feedback template to generate test feedback information.

8. An intelligent testing system for a cluster server, characterized in that: The system includes a real-time monitoring and processing module, a test data extraction module, a virtual test analysis module and a test comparison analysis module, wherein: A real-time monitoring processing module is used to perform real-time monitoring on the target cluster server, obtain real-time monitoring data, perform virtual test matching on the real-time monitoring data, and intercept virtual test data; A test data extraction module, used to identify the data type of the virtual test data and extract test requirement data from the virtual test data; A virtual test analysis module, used to perform virtual test analysis according to the test requirement data, and calculate the execution performance value and queuing performance value of the target cluster server; The test comparison and analysis module is used to perform test comparison and analysis on the execution performance value and the queuing performance value based on preset standard performance data to generate test feedback information.

9. The intelligent testing system for cluster servers according to claim 8, characterized in that: The real-time monitoring processing module specifically includes: A cluster server determination unit, used to determine a target cluster server having a test requirement; A monitoring and recording unit, used to monitor and record the target cluster server in real time to obtain real-time monitoring data; A virtual test matching unit, used to perform virtual test matching on the real-time monitoring data and determine a test matching period; The data interception unit is used to intercept virtual test data from the real-time monitoring data according to the test matching period.

10. The intelligent testing system for cluster servers according to claim 8, characterized in that: The test data extraction module specifically includes: A task identification unit, used to identify the virtual test data and determine the test task; A request identification unit, used to identify multiple test requests corresponding to the test task; A related test data extraction unit, configured to extract related test data from the virtual test data according to the plurality of test requests; The test requirement data extraction unit is used to extract the test requirement data from the relevant test data according to a plurality of preset requirement data types.

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